25 citations · 74 across the 17 of their papers we have counts for
7 papers · 1 filter
Towards a General Intelligence and Interface for Wearable Health Data
Girish Narayanswamy, Maxwell A. Xu, A. Ali Heydari +37
While ubiquitous wearable sensors capture a wealth of behavioral and physiological information, effectively transforming these signals into personalized health insights is challeng…
An AI Co-Data-Scientist for Prioritizing Candidate Biomarkers from Wearable Sensor Data
Yubin Kim, Salman Rahman, Samuel Schmidgall +33
Wearable devices generate continuous physiological and behavioral data, but converting these signals into clinically reviewable biomarker hypotheses remains labor-intensive. We int…
Towards a Science of Scaling Agent Systems
Yubin Kim, Ken Gu, Chanwoo Park +17
Agents, language model-based systems capable of reasoning, planning, and acting are widely adopted in real-world tasks, yet how their performance changes as these systems scale acr…
The Anatomy of a Personal Health Agent
A. Ali Heydari, Ken Gu, Vidya Srinivas +35
Health is a fundamental pillar of human wellness, and the rapid advancements in large language models (LLMs) have driven the development of a new generation of health agents. Howev…
Inferring Events from Time Series using Language Models
Mingtian Tan, Mike A. Merrill, Zack Gottesman +3
A common goal in analyzing time series data is to understand how events cause observed variations. We study whether Large Language Models (LLMs) can infer natural language events a…
Towards a Personal Health Large Language Model
Justin Cosentino, Anastasiya Belyaeva, Xin Liu +31
In health, most large language model (LLM) research has focused on clinical tasks. However, mobile and wearable devices, which are rarely integrated into such tasks, provide rich,…
Transforming Wearable Data into Personal Health Insights using Large Language Model Agents
Mike A. Merrill, Akshay Paruchuri, Naghmeh Rezaei +17
Deriving personalized insights from popular wearable trackers requires complex numerical reasoning that challenges standard LLMs, necessitating tool-based approaches like code gene…